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tracel-ai

tracel-ai/models

A collection of deep learning models and examples built with the Burn Rust deep learning framework, including official and community contributions.

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What is it?

This repository collects deep learning models and example code implemented with Burn, a deep learning framework written in Rust. It covers image classification models such as ResNet, SqueezeNet and MobileNetV2, object detection with YOLOX, and language and embedding models such as ALBERT, MiniLM and RoBERTa.

Beyond the official models, the page lists a set of community-built projects in separate repositories, including Whisper speech recognition, Llama 2, Stable Diffusion, RWKV, SSD and Wav2Vec 2.0 ports. Each official model lives in its own subdirectory and comes with its own usage notes.

The models are distributed under MIT and Apache-2.0 terms, and community projects may carry their own licenses.

Key features

  • 01Official implementations of image classification models including ResNet, SqueezeNet and MobileNetV2.
  • 02Object detection with YOLOX and language models such as ALBERT, MiniLM and RoBERTa.
  • 03Community ports of Whisper, Llama 2, Stable Diffusion, RWKV and other models.
  • 04Each official model sits in its own directory for independent use.
  • 05Built on the Rust-based Burn deep learning framework.

Use cases

  • Learning how to define and run common vision or NLP models in Rust with Burn.
  • Running image classification or object detection inside a Rust application without Python.
  • Finding Rust ports of speech recognition or language models built on Burn.

Things to know

  • Community models linked here may fall under different licenses than the repository's MIT/Apache-2.0 terms.

In collections

Computer vision libraries & toolsNatural language processing tools & libraries

Topics

#deep-learning#rust#machine-learning#computer-vision#nlp#examples

FAQ

What is models?
A collection of deep learning models and examples built with the Burn Rust deep learning framework, including official and community contributions. This repository collects deep learning models and example code implemented with Burn, a deep learning framework written in Rust. It covers image classification models such as ResNet, SqueezeNet and MobileNetV2, object detection with YOLOX, and language and embedding models such as ALBERT, MiniLM and RoBERTa.
Is models free to use? What license does it have?
models is open source under the Apache-2.0 license. Check the license terms before using it in commercial products.
Is models still maintained?
Actively maintained. The last commit to models was on Oct 26, 2026.
What can I use models for?
Learning how to define and run common vision or NLP models in Rust with Burn. Running image classification or object detection inside a Rust application without Python. Finding Rust ports of speech recognition or language models built on Burn.
Where can I get models?
The source code and installation instructions are on GitHub: https://github.com/tracel-ai/models

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